59 results about "Torque optimization" patented technology

The invention provides a tractor semitrailer full-working-condition active stability control system and method, and belongs to the technical field of vehicle engineering. The system comprises a kinetic model module, a reference quantity determination module and an active stability controller module. The dynamic model module constructs a linear three-degree-of-freedom tractor semitrailer model, a hub motor model and a longitudinal driver model. The reference quantity determination module generates an ideal state value according to the steady state condition of the system and corrects the ideal state value in combination with the road attachment condition. The active stability controller module is divided into three layers, an MIMO-IMFAC controller calculates additional yawing moment, a torque optimization controller optimizes tire load distribution through a quadratic programming algorithm, and a driving / braking torque distribution controller preferentially uses regenerative braking and dynamically adjusts braking torque of the semitrailer according to the yawing moment. By adopting the control system and the control method, the stability and the dynamic response capability of the vehicle under complex working conditions are remarkably improved.

The invention discloses an intelligent control method and system for a motor driver, and the method comprises the steps: building an acoustoelectric incidence matrix through collecting harmonic current and sound pressure fluctuation data in the operation process of a motor, and forming a fault feature library; identifying an available fault mode to determine an energy collection point, and performing phase deviation processing on the collection point to generate an auxiliary driving signal; performing spectrum analysis on the sound pressure fluctuation data to obtain an acoustic characteristic spectrum, extracting an efficiency indication tone through characteristic decomposition, mapping the efficiency indication tone into a torque optimization parameter, and establishing a noise reduction control table; performing spectrum analysis on the enhanced control domain to identify a high-energy frequency band, executing a frequency shift operation to generate a safety frequency band signal, and forming a multi-frequency band management strategy in combination with a noise reduction control table; a management strategy is decomposed into parallel control flows for sequential staggered arrangement, and an energy-saving control matrix is generated; and generating a PWM control signal based on the matrix, carrying out edge reconstruction, and obtaining a softened edge waveform through an anti-resonance injection technology to complete intelligent control of the motor driver.

The invention discloses an outer rotor permanent magnet synchronous motor torque optimization method, which comprises the following steps: 1) design parameter selection: selecting key characteristics of a motor stator slot as design parameters, including slot shoulder height Hs1, tooth length Hs2, chord length Bs0 and slot shoulder width Bs1; 2) finite element model construction: establishing a multi-target finite element model with cogging torque, torque pulsation and average torque as targets; 3) establishing an analytic model: establishing the analytic model of the motor torque by using an energy method and a repetitive unit method, and comparing the analytic model with the finite element model to verify the accuracy of the analytic model; 4) response surface model construction: based on the simulation data of the finite element model, performing finite element analysis by adopting a central composite design CCD, constructing a response surface model, performing sensitivity analysis on design variables, and determining the influence of each variable on an optimization target; and 5) optimization efficiency improvement: determining optimal configuration in a design space by using an adaptive genetic aggregation algorithm AGA, and achieving a multi-objective optimization effect.

The invention relates to the technical field of rail transit trains, and provides a motor torque distribution method, device and equipment for independent rotating wheels of a train, and the method comprises the steps: obtaining a state-space equation taking an independent wheel set and carriage movement as a research object; determining constraint conditions of the torque optimization function based on the state-space equation; determining a torque optimization function according to the train parameters and the wheel parameters; determining a torque distribution instruction of each wheel motor by taking minimization of a torque optimization function as a target based on a constraint condition; and controlling the motor torque output of each independent rotating wheel according to the torque distribution instruction. According to the method, the problem that guiding control and creep control are difficult to cooperate is solved, and the train operation stability and the wheel rail adhesion utilization rate are improved.

The invention discloses a multi-axis distributed driving vehicle torque distribution method based on a conditional solution method. The method comprises the following steps: initializing; designing a torque optimization distribution equation; solving a torque optimization distribution equation; and performing torque control. On the basis of the relation between the longitudinal driving force and the yawing moment of the vehicle and torque distribution, the influence of a tire attachment ellipse, the coupling problem of the longitudinal driving force and the lateral force of the tire and the problem that the vehicle is prone to instability under the nonlinear working condition are considered; a torque optimal distribution equation considering safety constraints such as the road adhesion coefficient and the maximum torque output capacity of the hub motor is designed, and reasonability, reliability and safety of the multi-axis distributed driving vehicle in torque optimal distribution are ensured. According to the method, a solution thought is provided for solving the real-time optimal feasible solution of torque distribution, and the distribution optimality, the solution real-time performance, the torque control precision, the stability and the robustness of the torque optimization distribution of the multi-axis distributed driving vehicle are guaranteed.

The invention discloses a pipeline flange sealing surface bolt fixed-torque fastening method, and relates to the technical field of pipeline fastening, and the method comprises the following steps: S1, collecting the roughness of a bolt hole sealing surface, constructing a scattering matrix, and obtaining a surface fluctuation main directivity index; s2, similar channels are judged according to the roughness Euclidean distance, and connectivity weights between the channels are constructed; s3, mapping the roughness and the surface fluctuation main directivity index into equivalent stiffness to calculate weighted stiffness; s4, calculating a load collaboration degree in combination with a spectrogram structure consistency index and a force distribution dispersion; s5, processing the residual stress time sequence data, and adjusting residual stress distortion in combination with the load collaboration degree and the weighted stiffness; and S6, according to the multi-target evaluation indexes, obtaining an optimal torque value by adopting a hybrid heuristic multi-target optimization algorithm, and applying the optimal torque in stages. By adjusting the pre-tightening force and the torque of the bolt hole, the mechanical behavior of the system is optimized, and the uniformity and the stability of the fastening process are improved by adopting a multi-objective optimization algorithm.

This application discloses an online identification method, apparatus, aircraft, and computer-readable storage medium for aircraft parameters, relating to the field of aircraft technology. The method includes: acquiring first parameters of the aircraft under low-frequency control commands; iteratively calculating an optimization function based on the first parameters to obtain a control efficiency optimization matrix; updating the optimization function based on the control efficiency optimization matrix; acquiring second parameters of the aircraft under variable-frequency control commands; iteratively calculating the updated optimization function based on the second parameters to obtain a gyroscopic torque optimization matrix and a transfer function optimization matrix; and determining a target control efficiency matrix, a target gyroscopic torque matrix, and a target transfer function matrix based on the control efficiency optimization matrix, the gyroscopic torque optimization matrix, and the transfer function optimization matrix. This application enables online identification of aircraft characteristic parameters through optimization functions, improving the convenience of aircraft parameter identification and allowing the aircraft to achieve optimal flight performance under different operating conditions.

The invention discloses a hybrid electric vehicle cooperative energy-saving control method and a hybrid electric vehicle cooperative energy-saving control system, which are used for constructing an integrated control system of vehicle-road cooperative information look-ahead-upper-layer vehicle speed planning-lower-layer ECMS-MPC torque optimization-upper-lower-layer closed-loop cooperative feedback aiming at complex working conditions of urban roads including signal lamp intersections, congested road sections and the like. The core defects of the prior art in the aspects of information dimension, working condition adaptability and control architecture are accurately overcome, and multi-target collaborative optimization of fuel consumption, traffic efficiency, driving comfort and battery life is achieved.

The invention discloses a screwdriver torque optimization control method based on a neural network. The method comprises the following steps: constructing a contact state diagram of a whole tightening process; node and edge features are extracted by using an isotropic graph neural network, and the clamping force variation is predicted; calculating an energy consistency condition based on a screw tightening physical model and updating edge features; inputting the updated state into the dimension raising dynamic model, and predicting a future state sequence; constructing a model prediction control optimization problem in combination with existing multi-dimensional constraint conditions, and generating an optimal torque instruction sequence; and judging a slip risk based on online gating, and executing a torque reduction and maintenance strategy. According to the method, the physical constraint and the deep learning model are combined, and high precision and high stability of torque control are achieved.

This invention discloses a mechanical leg, a robot, and a torque optimization design method. The mechanical leg includes a first transmission arm, a second transmission arm, and a transmission assembly. The first transmission arm connects to the robot's body and includes a frame with a guide groove extending along its length. The second transmission arm is rotatably connected to the first transmission arm. The transmission assembly includes a knee joint drive motor, a lead screw, a slide block, a connecting rod, and a crank. One end of the lead screw is connected to the output shaft of the knee joint drive motor, and the other end passes through the frame. The slide block is fitted onto the lead screw and has a guide portion that inserts into the guide groove. Rotation of the lead screw drives the slide block to move axially along the lead screw. One end of the connecting rod connects to the slide block, and the other end connects to the second transmission arm via the crank. This mechanical leg, by combining a ball screw mechanism and a crank-slide block mechanism, effectively amplifies the torque of the knee joint drive motor.

This invention discloses a motion control method for a six-wheeled lunar rover based on a hierarchical control structure. The method includes establishing a six-wheeled lunar rover model and a hierarchical control framework comprising a state reference layer, a torque decision layer, and a torque distribution layer. In the state reference layer, a two-degree-of-freedom single-track model is constructed to calculate the ideal yaw rate and center-of-gravity sideslip angle. In the torque decision layer, a double-power-law approach is designed to calculate the longitudinal velocity tracking error, yaw rate tracking error, and center-of-gravity sideslip angle tracking error; a sliding mode control method is used to calculate the generalized longitudinal force, lateral force, and yaw moment. In the torque distribution layer, an objective function is constructed based on the optimal control principle, and the torque distribution for the six wheels is optimized under the constraints of minimizing tire load rate and total motor energy consumption. This invention achieves motion stability control and collaborative optimization through a hierarchical control architecture, a sliding mode variable structure algorithm, and dynamic torque optimization distribution, providing an effective solution for torque control strategies in lunar exploration missions.

A kind of electric vehicle Tip-in anti-collision gear control system and control method, belong to the technical field of automobile driving performance optimization, wherein the electric vehicle Tip-in anti-collision gear control system, including the detection component that detection loosens acceleration pedal and then carries out Tip-in operation and makes the detection component of whole car gear impact risk state, detection component is connected with motor controller by whole car controller to control motor gear front and reducer gear reverse side keeps meshing, the beneficial effects of the present application are, the present application increases reasonable gear torque to motor in the process of vehicle sliding, optimizes the whole car gear impact feeling when Tip-in operation again in the process of low-speed sliding under non-energy recovery state, further improves the driving comfort of whole car.

The invention discloses a wheel-foot robot climbing control method and system based on attitude and torque optimization, and relates to the technical field of robot control. The method comprises the steps that the gravity center of a robot trunk serves as the moment center, and a statics model of a wheel-foot robot on a slope is constructed; quantitatively analyzing the influence of gravity projection, wheelbase and station height of the robot on torque distribution of front and rear wheels, and establishing a torque distribution ratio formula; determining an optimal gravity center projection distance ratio, an optimal axle distance and an optimal station height by taking torque balance as a target; in the actual climbing process of the wheel-foot robot, the projection position of the gravity center of the robot body is obtained in real time, the posture of the wheel-foot robot is adjusted and controlled according to the projection position, the projection position is always located in a safe area of the supporting polygon, and meanwhile the optimal gravity center projection distance ratio, the axle distance and the station height are combined according to the projection position. And torque output of front and rear wheels of the wheel-foot robot is regulated to realize stable climbing. The problem that the wheel-foot robot turns on one side and slips frequently in the process of advancing on the slope can be solved.

The present application relates to the motor technical field, especially a kind of motor tooth slot torque optimization method, device, equipment and storage medium.It is by constructing motor simulation model, and parameter scanning is carried out to motor simulation model, obtains scanning data;Based on scanning data, fitting function is constructed;According to the geometric parameters of motor simulation model, determine parameter boundary condition;According to parameter boundary condition and fitting function, determine target auxiliary slot parameter.The present application is by constructing motor simulation model first, and parameter scanning is carried out to motor simulation model, obtains scanning data, then according to scanning data, fitting function is constructed, reduces the computing power cost, according to the geometric parameters of motor simulation model, determine parameter boundary condition, finally according to fitting function and parameter boundary condition, determine target auxiliary slot parameter, to make the auxiliary slot opened according to the target auxiliary slot parameter can guarantee the output torque of motor and reduce the tooth slot torque of motor.

A torque optimization system for an electrified vehicle having an electrified powertrain including three electric motors a, b, and c and an additional torque generating system includes a set of sensors configured to measure a set of operating parameters of the electrified vehicle and a control system configured to determine a torque relationship between electric motors b and c, solving a three-dimensional (3D) optimization problem for the electrified powertrain, the 3D optimization problem defining torques generatable by one of electric motors b and c, electric motor a, and the additional torque generating system, determine torque commands for the three electric motors a, b, and c and the torque generating system based on the solving of the 3D optimization problem, the determined torque relationship, and the set of operating parameters, and control the electrified powertrain based on the determined torque commands.

The application discloses an intelligent control method and system of a motor driver, which comprises the following steps: collecting harmonic current and sound pressure fluctuation data in the motor operation process, constructing a sound-electricity correlation matrix to form a fault feature library; identifying available fault modes to determine energy collection points, and performing phase offset processing on the collection points to generate auxiliary driving signals; performing frequency spectrum analysis on the sound pressure fluctuation data to obtain acoustic characteristic spectrum, extracting efficiency indicating sound through characteristic decomposition and mapping into torque optimization parameters, and establishing a noise reduction control table; performing frequency spectrum analysis on an enhanced control domain to identify high-energy frequency bands, performing frequency shift operation to generate safe frequency band signals, and combining the noise reduction control table to form a multi-frequency band management strategy; decomposing the management strategy into parallel control flows for time sequence interleaving arrangement to generate an energy-saving control matrix; generating a PWM control signal based on the matrix and performing edge reconstruction, obtaining a softened edge waveform through anti-resonance injection technology, and completing intelligent control of the motor driver.

The present invention relates to the technical field of shield tunnel construction, and specifically discloses an intelligent regulation method for shield tunnels with an ultimate radius in a narrow space, including: obtaining the state information of the shield machine; collecting formation pressure, moisture content, and soil deformation data to obtain formation characteristic information; analyzing and obtaining an optimal construction adjustment strategy based on the formation characteristic information; based on the optimal construction adjustment strategy, using deep reinforcement learning combined with fuzzy PID control to calculate the optimal tunneling trajectory of the shield machine, and obtaining an adaptable construction plan for the ultimate radius in a narrow space; the present invention jointly optimizes the trajectory of the shield machine based on deep reinforcement learning combined with fuzzy PID control, realizes dynamic attitude correction, and reduces the deviation of the tunneling trajectory. The multi-sensor data fusion improves the accuracy of attitude estimation, realizes the reduction of the shield attitude angle error, effectively reduces the number of manual interventions, and improves the construction efficiency; the automatic thrust and torque optimization control avoids attitude mutations caused by formation changes and improves the stability of the shield machine.

This application discloses a method for active thermal management and torque coordinated control of motors in a large eVTOL system, relating to the field of electric vertical takeoff and landing aircraft control technology. The disclosed method for active thermal management and torque coordinated control of motors in a large eVTOL system acquires flight mission data and real-time status data, calculates thermal load assessment data, determines multi-objective optimization weight configuration data, and inputs torque optimization commands to a dynamic optimizer, thereby realizing coordinated control of motor thermal management and torque output. This method can effectively prevent motor thermal imbalance, improve flight control accuracy and system reliability, and avoid failures caused by overheating.

The invention discloses an automobile composite braking torque optimal distribution method based on EMB multi-stage response characteristics. The method comprises the following steps that 1, all sensors collect data signals; step 2, calculating the required braking torque of the whole vehicle and distributing the front and rear braking torque; 3, judging whether the EMB intervenes or not: if the EMB needs to intervene, carrying out a step 4, and if the EMB does not need to intervene, directly carrying out a step 7; 4, primarily distributing a braking torque coefficient based on interval type-2 fuzzy control; step 5, discriminating an EMB working stage; step 6, carrying out secondary distribution on a braking torque coefficient based on EMB multi-stage response characteristics; 7, EMB / regenerative braking is implemented; and 8, whether braking is finished or not is judged. In the re-distribution process of the braking torque coefficient, the working characteristics that the braking torque of the EMB is vacant in the braking torque no-load stage and the braking torque is rapidly changed in the braking torque lifting stage are fully considered, and the braking recovery efficiency and the braking stability of the automobile are effectively improved.

The present invention provides a method and device for controlling the torque distribution of a vehicle, and relates to the field of automotive technology. In this application, the current state of the vehicle (braking or accelerating) is accurately identified based on the vehicle state information, such as vehicle speed, acceleration, battery parameters and other multivariate data, so that the control center can enter the corresponding control mode, which speeds up the response rate of the vehicle driving controller to accelerate or brake, so as to coordinate and control the torque distribution between motors and improve the overall working efficiency of the motors. Then, the inter-axle torque is optimized and distributed according to the vehicle state information and road condition information. The system performance is improved based on the trial-and-error interaction with the environment through reinforcement learning, based on the observation value and the analysis of the system behavior. The optimal control strategy is usually obtained with the goal of maximizing the cumulative reward function. It can not only improve the vehicle's handling stability and safety, but also has great potential in improving economy and the energy utilization rate of the vehicle.

The present invention provides a regenerative braking method and electromechanical system applicable to all operating conditions. The brake control unit receives brake pedal opening, vehicle speed, and wheel speed signals, calculates braking intensity using a fuzzy controller, obtains motor torque and hydraulic torque using a braking torque optimization distribution module, and determines whether a downshift is necessary using a downshift strategy module. The motor controller receives control instructions from the brake control unit and controls the motor to output the corresponding torque. The hydraulic controller receives control instructions from the brake control unit and controls the hydraulic brake system to output the corresponding hydraulic torque. The DHT controller receives control instructions from the brake control unit and controls the clutch and synchronizer to implement mode / gear switching. The downshift strategy module includes a downshift switching function consisting of the inverse of the objective function increment and a periodic penalty switching index to determine the downshift switching conditions. This invention effectively prevents frequent mode / gear switching and upshifting.

The application discloses a new energy automobile whole vehicle torque zero-crossing control method and system, a server and a medium, and relates to the technical field of new energy automobiles.The control method comprises the following steps: obtaining the current throttle opening of the vehicle, the actual torque of the rear motor, the required torque of the rear motor and the torque zero-crossing interval; when the required torque of the rear motor and the actual torque of the rear motor are both in the torque zero-crossing interval, adjusting the required torque of the front motor and the required torque of the rear motor according to a set torque distribution ratio; when at least one of the required torque of the rear motor and the actual torque of the rear motor is not in the torque zero-crossing interval, adjusting the required torque of the front motor and the required torque of the rear motor according to a preset data distribution table and the current throttle opening of the vehicle; controlling the rotation of the front motor according to the adjusted required torque of the front motor, and controlling the rotation of the rear motor according to the adjusted required torque of the rear motor. The required torques of the front motor and the rear motor are adjusted in different ways, and the torque zero-crossing jitter problem of the vehicle is optimized.

The application discloses a kind of vehicle torque optimization control method and system, including: vehicle acceleration process, judge whether engine is off-cylinder, if yes, according to the speed signal at this time to determine air-fuel ratio, as target air-fuel ratio;Otherwise, directly set value to target air-fuel ratio, the set value is equal to or close to the value of optimum air-fuel ratio.The application in vehicle acceleration process, when engine off-cylinder, according to the speed signal measured at this time, off-cylinder air-fuel ratio calibration under different speeds is carried out, control air-fuel ratio is around 1, reduce the performance of mis-addition, optimize the acceleration time per 100 kilometers to improve, air-fuel ratio is no longer thickened, torque performance is smooth, reach the goal of acceleration time per 100 kilometers.

The present application relates to cable sheath extrusion equipment technical field, especially a kind of based on torque optimization's double screw grouting extruder and its control system, including extrusion assembly, cladding assembly and detection assembly and information acquisition unit, processing unit and execution unit, according to the feed speed of cable blank adjustment extrusion assembly's extrusion rate, guarantee sheath thickness and continuity, guarantee the processing precision of cable, reduce processing error, different specifications thick and thin cable blank are automatically identified, match corresponding sheath thickness, gear can move up and down, when cable blank appears fault defect, automatically close conical block and conical cavity, prevent sheath continue production, realize the automatic detection and alarm of defect, reduce product defect, improve cable production quality, pass through the running state of cable blank by gyro wheel judgment, adapt different driving motor input power, to optimize the torque of two transmission screws, realize best extrusion effect, improve production intelligentization and production efficiency.

The invention belongs to the technical field of wind power generation control, and discloses a wind turbine generator torque optimization method and a related device, and the method comprises the steps: obtaining the state data of a wind turbine generator; according to the state data of the wind turbine generator, a rotating speed control value of the wind turbine generator is obtained through a pre-trained generator torque control model; wherein the generator torque control model is constructed on the basis of a reinforcement learning model, a reward function of the generator torque control model is constructed on the basis of dynamic weighted generating capacity reward and mechanical stress punishment, and the weight of dynamic weighting is determined on the basis of the system health degree of a wind turbine generator. Based on the autonomous optimization potential of the reinforcement learning technology, the method has good adaptability, and can accurately and quickly realize generator torque optimization. By adopting a multi-target collaborative optimization reward function design, equipment health state monitoring data are effectively fused, the balance between power generation efficiency and mechanical loss is realized, and stable operation of a generator of a wind turbine generator is ensured.

The invention discloses a real-time torque optimal distribution method and device and a storage medium, and relates to the field of automobile torque intelligent distribution. The method comprises the steps that a solver used for solving the optimal additional torque of four wheels of the vehicle and a predictor used for determining the initial additional torque are constructed; training the predictor through a training set to predict an initial additional torque; and when the difference between the initial additional torque predicted by the trained predictor on the test set and the optimal additional torque obtained by the solver through the test set is below the specified tolerance, determining that the initial additional torque obtained by the predictor is available. According to the method, the advantages of the neural network and the multi-objective optimization torque vector distribution algorithm are fully coupled and played, the appropriate initial additional torque is automatically predicted by coupling neural network prediction and multi-objective optimization iteration solution, it is ensured that the initial additional torque is close to the optimal additional torque in the numerical value and iteration direction, and therefore the calculation speed is remarkably increased, and the calculation efficiency is improved. And the computing power is reduced.

A torque optimization system for an electrified vehicle having an electrified powertrain including three electric motors a, b, and c and an additional torque generating system includes a set of sensors configured to measure a set of operating parameters of the electrified vehicle and a control system configured to determine a torque relationship between electric motors b and c, solving a three-dimensional (3D) optimization problem for the electrified powertrain, the 3D optimization problem defining torques generatable by one of electric motors b and c, electric motor a, and the additional torque generating system, determine torque commands for the three electric motors a, b, and c and the torque generating system based on the solving of the 3D optimization problem, the determined torque relationship, and the set of operating parameters, and control the electrified powertrain based on the determined torque commands.

The invention belongs to the technical field of design of vehicle dynamics control, and discloses a distributed electric drive vehicle torque optimal distribution method, which comprises the following steps: firstly, building a vehicle dynamics model through a vectorization modeling method, and then, building a torque optimal distribution solver according to constraint conditions; and parameters in the solver are traversed and solved to obtain a torque optimal distribution table for off-line calculation, table data are stored in a VCU, and off-line calculation of torque optimal distribution of the four-wheel drive vehicle is achieved. According to the torque optimal distribution algorithm and the implementation method, the dynamic response speed and the control stability of the vehicle are improved, and meanwhile the problem that the calculation power of a vehicle control unit is insufficient is effectively solved.

The invention discloses an automatic motor calibration algorithm based on variable carrier frequency and composite modulation, and the algorithm specifically comprises the steps: 1, employing a switching frequency capable of covering all working conditions and an SVPWM modulation mode, building a motor twin trawling rack test system, guaranteeing the normal connection of a motor controller with a power analyzer and a CAN communication system, and enabling the motor controller to be connected with a power analyzer; control instruction sending, torque data acquisition and system efficiency real-time transmission are realized; 2, calibrating a low rotating speed interval to obtain maximum torques and corresponding angles under different currents; 3, calibrating a high rotating speed interval so as to adapt to torque optimization under the limit voltage; step 4, system efficiency optimization calibration is carried out to determine an optimal modulation mode and switching frequency; step 5, back electromotive force monitoring and thermal management; step 6, switching frequency processing and modulation mode correction; and step 7, integrating the calibration data of all the working condition points, extracting the optimal system efficiency point under each working condition and the corresponding modulation mode and switching frequency, generating a motor control program file according to the optimal parameters, and completing all-working-condition calibration.

The invention discloses a motor failure fault-tolerant torque distribution system for a distributed driving electric vehicle, and belongs to the technical field of vehicle control. The invention aims to solve the technical problem of man-machine conflict caused by tension misoperation of a driver due to sudden change of dynamic response of a vehicle after a motor fault, and the system comprises a data acquisition and processing unit, a self-correction module, a driver intention and cognitive state cognition module, a predictive deduction module and a man-machine collaborative torque optimization module. The self-correction module identifies motor fault evolution characteristics on line and corrects a digital twinborn model in real time to reproduce fault dynamics, the predictive deduction module is based on a corrected pathological digital twinborn body and is coupled with a driver model, potential man-machine conflicts are predicted and restrained, the stability of a vehicle is guaranteed, and meanwhile the reliability of the vehicle is improved. Smooth and predictable fault response is achieved, and the cooperative driving safety of the vehicle under the fault working condition is fundamentally improved.